Intelligent information conversion for automatic driving

ABSTRACT

Provided herein is technology relating to automated driving and particularly, but not exclusively, to an intelligent information conversion system and related methods for providing collaborative automatic driving to intelligent transportation systems, vehicle networking systems, collaborative management control systems, vehicle-road collaborative systems, automated driving systems, and the like.

This application claims priority to U.S. provisional patent applicationSer. No. 63/137,243, filed Jan. 14, 2021, which is incorporated hereinby reference in its entirety.

FIELD

Provided herein is technology relating to automated driving andparticularly, but not exclusively, to an intelligent informationconversion system and related methods for providing collaborativeautomatic driving to intelligent transportation systems, vehiclenetworking systems, collaborative management control systems,vehicle-road collaborative systems, automated driving systems, and thelike.

BACKGROUND

Autonomous vehicles that are capable of sensing the environment andnavigating without human input or with reduced human input are indevelopment and experimental testing. However, widespread implementationand large-scale commercial use of autonomous vehicles have been limitedby existing autonomous driving technologies that require complex andredundant on-board systems and roadside systems.

SUMMARY

Provided herein is technology related to systems and methods for anintelligent information conversion system (IICS), e.g., that finds usein supporting automatic driving (e.g., collaborative automated driving).Embodiments of the IICS and related methods provided herein supportvehicle-road collaborative automatic driving and effectively reducecomplexity and redundancy of automated driving systems. Accordingly, theIICS technology provided herein promotes the large-scale implementationof autonomous vehicles.

In some embodiments, the IICS finds use for any type of automateddriving system and/or any type of intelligent road infrastructure system(IRIS). In some embodiments, the IICS finds use for a ConnectedAutomated Vehicle Highway (CAVH) system, e.g., as described in U.S. Pat.No. 10,380,886, which is incorporated herein by reference. For example,in some embodiments, the IICS provides systems and methods to realizereal-time and dynamic information exchange between the road end (e.g.,road infrastructure) and the vehicle end (e.g., CAV) of an automateddriving system by converting information into a form for use by CAVhaving a range of intelligence levels (e.g., vehicle automation levelV1.5, V2, V3, or V4) when they enter road segments equipped with roadinfrastructure, e.g., IRIS (see U.S. Pat. Nos. 10,867,512 and/or10,692,365, each of which is incorporated herein by reference).

In some embodiments, the IICS provides a “code book” for convertingvarious types of information (e.g., by encoding and decodinginformation), e.g., for use by vehicles (e.g., CAV) having a range ofintelligence levels (e.g., V1, V1.5, V2, V3, and/or V4) and for aplurality of vehicles (e.g., CAV) having a range of intelligence levels(e.g., V1, V1.5, V2, V3, and/or V4).

In some embodiments, the IICS provides sensing, decision-making, andcontrol instructions to CAV for performing driving tasks. In someembodiments, the IICS is applicable for all road types and facilitatesthe intelligent allocation of automatic driving, enhances system servicelevels, and increases the levels of information, intelligence, and/orcoordination for automatic driving and CAV.

Accordingly, in some embodiments, the technology provides an intelligentinformation conversion system (IICS) configured to connect an automaticdriving system (ADS) and a connected and automated vehicle (CAV); andprovide real-time dynamic information exchange between ADS and CAV. Insome embodiments, wherein the ADS comprises an intelligent roadsideinfrastructure system (IRIS). In some embodiments, the IICS improves theservice level of an ADS from a first service level to a second servicelevel, wherein the first service level is not adequate to provideautomatic driving for a CAV and the second service level is adequate toprovide automatic driving for the CAV. In some embodiments, the IICS isconfigured to connect any ADS of a plurality of ADS and any CAV of aplurality of CAV; and provide real-time dynamic information exchangebetween any ADS of a plurality of ADS and any CAV of a plurality of CAV.

In some embodiments, the IICS comprises a code book providing astandardized format for information exchange. In some embodiments, theIICS is configured to sort information in a code book string. In someembodiments, the IICS is configured to encode information into a codebook string. In some embodiments, the IICS is configured to decodeinformation from a code book string. In some embodiments, the IICScomprises an encoding or encoding/decoding module configured to encodeinformation into a code book string. In some embodiments, the IICScomprises an encoding/decoding module configured to decode informationfrom a code book string.

In some embodiments, the standardized format for information exchangecomprises a sequence of integers, wherein each integer has a valuecorresponding to a value of a category including vehicle automationlevel, original equipment manufacturer, vehicle brand, vehicle modelyear, vehicle type, road category, highway level, urban road level, roadintelligence level, information function level, information category I(frequency), information category II (safety demand), informationcategory III (precision), information category IV (scope), informationcategory V (static and dynamic), or information category VI (name). Insome embodiments, the standardized format for information exchangecomprises a sequence of sixteen integers. In some embodiments, the IICScomprises an encoding/decoding module configured to facilitate real-timedynamic information interaction between CAV and ADS. In someembodiments, the IICS comprises an encoding/decoding module configuredto facilitate real-time dynamic information interaction between CAV androad infrastructure. In some embodiments, the IICS comprises anencoding/decoding module configured to exchange information between CAVand ADS by encoding information received from a CAV and/or ADS into acode book string; and by decoding a code book string into informationfor transmission to a CAV and/or ADS.

In some embodiments, the code book string has a format provided by acode book standardized format for information exchange. Accordingly, insome embodiments, the code book string comprises a sequence of integers,wherein the position of an integer within the code book string (e.g.,position 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16 fromleftmost to rightmost position within the code book string) isassociated with a category of information and/or a descriptor of acategory of information that is vehicle automation level, originalequipment manufacturer, vehicle brand, vehicle model year, vehicle type,road category, highway level, urban road level, road intelligence level,information function level, information category I (frequency),information category II (safety demand), information category III(precision), information category IV (scope), information category V(static and dynamic), or information category VI (name); and eachinteger has a value corresponding to a value of the category indicatedby the integer position. See, e.g., Table 1.

In some embodiments, the IICS comprises a road-side connector component(e.g., a data exchange interface connecting IICS and roadsideinfrastructure (e.g., IRIS)) configured to exchange information betweenthe IICS and roadside infrastructure (e.g., IRIS); and a vehicle-sideconnector component (e.g., a data exchange interface connecting IICS anda vehicle (e.g., CAV)) configured to exchange information between theIICS and a vehicle (e.g., CAV).

In some embodiments, the IICS comprises a supporting subsystemcomprising a cache subsystem and a power supply subsystem.

In some embodiments, the IICS is configured to provide service for anADS of any intelligence level.

In some embodiments, the IICS is configured to integrate into an IRISand/or a cloud platform.

In some embodiments, the IICS is configured to receive vehicleinformation and/or information demands from a vehicle. In someembodiments, the vehicle transmits vehicle information and/orinformation demands to the IICS. In some embodiments, the vehicle isdriving on a road comprising an intelligent infrastructure. In someembodiments, the vehicle is driving on a road serviced by an ADS. Insome embodiments, the vehicle is driving on a road serviced by an IRIS.In some embodiments, the vehicle comprises a vehicle intelligence unit(VIU). In some embodiments, the IICS comprises a vehicle-side connectorconfigured to receive vehicle information and/or information demandsfrom a vehicle and/or VIU.

In some embodiments, the IICS comprises an IRIS and the IRIS comprises ahierarchical structure comprising RIU configured to receive vehicle-sideinformation from IICS and to exchange data with a TCU; TCU configured toexchange data with RIU, other TCU, and TCC; and to perform data fusionand processing functions; and TCC configured to perform decision-makingand/or traffic control functions and to store data. In some embodiments,the TCC is provided in a cloud-based platform. In some embodiments, CAVcomprise a vehicle-end connector component. In some embodiments, thevehicle-connector component comprises an environment sensing moduleconfigured to sense the surrounding environment of a CAV; and/or tocollect data from external vehicle sensors; an internal environmentsensing module configured to sense the status of the CAV, to sense theinternal environment of the CAV, and to sense the driver status; and/orto collect data from internal vehicle sensors; a cognitive moduleconfigured to collect semantic information and/or cognitive informationdescribing the CAV environment; and/or a decision-making moduleconfigured to provide vehicle control decisions. In some embodiments,the cognitive module is configured to integrate vehicle sensorinformation and roadside infrastructure information from IICS. In someembodiments, vehicle sensor information and roadside infrastructureinformation from IICS comprises information describing the environmentof the CAV, obstacle types and locations, and/or vehicle drivingtrajectories. In some embodiments, the decision-making module isconfigured to make decisions based on stored data, stored controldecisions, and/or stored outcomes of control decision execution. In someembodiments, the decision-making module is configured to make decisionsbased on control instructions received from IRIS through IICS. In someembodiments, the environment sensing module is configured to integratedata and/or information from vehicle sensors with data and/orinformation from roadside infrastructure sensors obtained from IICS todescribe the vehicle environment and predict vehicle trajectory.

In some embodiments, IRIS is configured to issue control commands toexecution modules of CAV having an intelligence level of V1 or V1.5through the IICS; and the IRIS is configured to receive and/or store theresult of executing the control commands for data backup and/or machinelearning to adjust future control commands. In some embodiments, IRIS isconfigured to receive vehicle sensor information and/or data from IICS;receive roadside infrastructure sensor information and/or data; andprovide driving decisions and/or vehicle control instructions to IICS.In some embodiments, a TCU/TCC processes the vehicle sensor informationand/or data and/or the roadside infrastructure sensor information and/ordata. In some embodiments, a TCU/TCC provides driving decisions and/orvehicle control instructions to IICS. In some embodiments, the IRIScomprises an IRIS communications module, IICS comprises an IICScommunications module, and/or CAV comprises a CAV communications module;and the IRIS, IICS, and/or CAV communicate with each other using theIRIS communications module, the IICS communications module, and/or theCAV communications module. In some embodiments, IRIS, IICS, and/or CAVcommunicate with each other using dedicated short-range communication,4G cellular communication, 5G cellular communication, and/or 6G cellularcommunication. In some embodiments, the cache subsystem is configured tocache data received by the IICS. In some embodiments, the power supplysubsystem is configured to provide energy to the IICS.

In some embodiments, the IRIS comprises an RIU and the RIU comprises asensing module; an interaction module; and a communications module. Insome embodiments, the sensing module comprises a camera, radar, andother sensors, which collect traffic, and vehicle driving environmentinformation within the road section. In some embodiments, the radar ismicrowave radar. In some embodiments, the sensing module is configuredto collect traffic information and/or vehicle driving environmentinformation. In some embodiments, the interaction module is configuredto integrate data from the sensing module and the communication module;and/or to exchange data and/or information with the communicationmodule. In some embodiments, the communications module is configured toreceive data and/or information from the interaction module; and/or toexchange data and/or information with a TCU communication module.

In some embodiments, the IRIS comprises a TCU and the TCU comprises adata processing module; and a communication module. In some embodiments,the communications module is configured to exchange data and/orinformation with the data processing module and/or communication modulesof other TCU. In some embodiments, the TCU is a point TCU and/or asegment TCU. In some embodiments, the communications module does notcommunicate directly with the communication module of IICS. In someembodiments, the data processing module is configured to fuse datareceived from the communication module and traffic state information toproduce fused data; to process fused data; and to make decisions basedon the fused data. In some embodiments, the data received from thecommunication module comprises current traffic control information,vehicle road sensing information from a roadside communication module,and/or information from a TCU. In some embodiments, the traffic stateinformation comprises traffic flow information, traffic speedinformation, and/or traffic congestion information.

In some embodiments, the IICS is configured to assist CAV atintelligence level V1 or V1.5, wherein an IRIS and the IICS performinformation integration and decision-making; and send vehicle controlinstructions to CAV. In some embodiments, the TCC/TCU receives sensinginformation from a RIU and a VIU of a CAV, wherein the CAV drives on aroad serviced by infrastructure and needing assistance for automateddriving from the infrastructure; IRIS makes a decision based on the dataand/or information received from IICS describing the road environment,road geometry information, and/or vehicle driving information; andprovide control instructions to CAV through the IICS; and CAV performsvehicle control operations according to the control instructionsreceived by IICS. In some embodiments, information from roadside sensorsand/or infrastructure supports the decision-making of the TCC/TCU; andthe vehicle-end information provides feedback for verifying and/oradjusting future decision-making.

In some embodiments, the IICS is configured to assist CAV atintelligence level V2 or V3, wherein a VIU exchanges information withIICS based on the information requirements of a driving task; androadside data and/or information provided through IICS supports the VIUto complete a driving task. In some embodiments, the VIU is configuredto store roadside data and/or information provided through IICS toincrease accumulation of experience data for adapting driving to anincreased number of driving environments and scenarios. In someembodiments, the TCC/TCU receives sensing information from a RIU and aVIU of a CAV, wherein the CAV drives on a road serviced byinfrastructure and needing assistance for automated driving from theinfrastructure; IRIS transmits information and/or data to VIU throughIICS; and IRIS and VIU collaborate to provide control instructions toCAV. In some embodiments, the TCC/TCU receives information and/or datafrom roadside infrastructure and/or and vehicle-end information fromIICS. In some embodiments, the vehicle control system operates accordingto vehicle status information, road geometry information, target objectinformation, and/or the vehicle experience memory. In some embodiments,a vehicle control system collaborates with IRIS to provide operatinginstructions and/or vehicle control instructions to CAV. In someembodiments, IRIS collaborates with a VIU and/or vehicle on-boardcontrol system to provide operating instructions and/or vehicle controlinstructions to CAV.

In some embodiments, the IICS is configured to assist CAV atintelligence level V4 or above, wherein the IICS transmits roadsidesensing information and/or data to a VIU to support the CAV vehiclecontrol system. In some embodiments, TCC/TCU receives sensinginformation and/or data from a RIU. In some embodiments, TCC/TCU doesnot receive information and/or data from VIU. In some embodiments,TCC/TCU and the on-board control system sense traffic information and/ordriving behavior information independently; and/or vehicle controlsystem receives sensing information from the VIU and roadside sensinginformation transmitted by IICS, and makes a vehicle control decisionindependently. In some embodiments, roadside sensing information istransmitted to VIU through IICS; and the roadside sensing information isthen transmitted to the on-board control system to support the vehiclecontrol system in providing vehicle control instructions and/or decisioninformation to the execution module.

Also provided herein are methods employing any of the systems describedherein for the management of one or more aspects of automated driving ofa CAV and/or for the management of one or more aspects of trafficcontrol. The methods include those processes undertaken by individualparticipants in the system (e.g., drivers, public or private local,regional, or national transportation facilitators, government agencies,etc.) as well as collective activities of one or more participantsworking in coordination or independently from each other.

For example, in some embodiments, methods are performed by an IICS asdescribed herein (e.g., an IICS configured to perform the methods). Forexample, in some embodiments, the technology provides a method forinformation exchange between a CAV and IRIS. In some embodiments,methods comprise transmitting vehicle-end information and/or vehicleinformation demands from a vehicle to an IICS; encoding the vehicle-endinformation and/or vehicle information demands by the IICS to produceencoded vehicle-end information and/or vehicle information demands;transmitting the encoded vehicle-end information and/or vehicleinformation demands to IRIS; and parsing the encoded vehicle-endinformation and/or vehicle information demands by IRIS to producedecoded vehicle-end information and/or vehicle information demands. Insome embodiments, transmitting vehicle-end information and/or vehicleinformation demands from a vehicle to the IICS comprises transmittingthe vehicle-end information and/or vehicle information demands from aVIU of the vehicle. In some embodiments, transmitting vehicle-endinformation and/or vehicle information demands from a vehicle to theIICS comprises transmitting the vehicle-end information and/or vehicleinformation demands through a connector of the IICS. In someembodiments, vehicle-end information comprises vehicle accessverification information, vehicle sensing information and/or data,vehicle control command information, vehicle status information, and/orvehicle driving task execution information. In some embodiments, vehicleinformation demands comprise one or more information demands in thecategories of frequency, safety demand, precision, scope, and/or staticor dynamic. In some embodiments, encoded vehicle-end information isencoded in a code book standardized format for information exchange. Insome embodiments, transmitting the encoded vehicle-end information toIRIS comprises transmitting the encoded vehicle-end information througha connector of the IICS. In some embodiments, vehicle sensinginformation and/or data comprises data from vehicle external sensorsand/or data from vehicle interior sensors.

In some embodiments, methods further comprise fusing by IRIS the decodedvehicle-end information and/or vehicle information demands withinformation and/or data from roadside infrastructure to produce fusedinformation; encoding the fused information to produce encoded fusedinformation; transmitting the encoded fused information from IRIS toIICS; decoding by IICS the encoded fused information to produce decodedfused information and/or vehicle information demands; and transmittingthe decoded fused information and/or vehicle information demands fromIICS to CAV. In some embodiments, transmitting the encoded fusedinformation from IRIS to IICS comprises transmitting the encoded fusedinformation through a connector of the IICS. In some embodiments,transmitting the decoded fused information and/or vehicle informationdemands from IICS to CAV comprises transmitting the decoded fusedinformation and/or vehicle information demands through a connector ofthe IICS. In some embodiments, the encoded fused information is encodedin a code book standardized format for information exchange.

In some embodiments, the IICS is configured to perform a method ofclassifying information based on the frequency of update of theinformation to assign a value to information category I (frequency) ofhigh frequency, medium frequency, or low frequency. In some embodiments,the IICS is configured to perform a method of classifying informationbased on the safety demand of the information to assign a value toinformation category II (safety demand) of high safety demand, mediumsafety demand, or low safety demand. In some embodiments, the method ofclassifying information based on the safety demand of the informationcomprises assessing the importance of the information for decisionmaking, motion planning, and/or control of automated vehicles. In someembodiments, the IICS is configured to perform a method of classifyinginformation based on precision of the information to assign a value toinformation category III (precision) of high precision, mediumprecision, or low precision. In some embodiments, the method ofclassifying information based on precision of the information comprisesassessing a driving scenario, driving task, and/or vehicle intelligencelevel. In some embodiments, the IICS is configured to perform a methodof classifying information based on the scope of the information toassign a value to information category IV (scope) of macroscopic,mesoscopic, or microscopic. In some embodiments, macroscopic informationcomprises road network level information; mesoscopic informationcomprises road section level information; and/or microscopic informationcomprises vehicle level information. In some embodiments, the IICS isconfigured to perform a method of classifying information based on thestatic or dynamic characteristics of the information to assign a valueto information category V (static or dynamic) of static dynamic. In someembodiments, static information comprises information that is unchangedduring the operation of the vehicle; and/or dynamic informationcomprises information that changes during the operation of the vehicle.

Some portions of this description describe the embodiments of thetechnology in terms of algorithms and symbolic representations ofoperations on information. These algorithmic descriptions andrepresentations are commonly used by those skilled in the dataprocessing arts to convey the substance of their work effectively toothers skilled in the art. These operations, while describedfunctionally, computationally, or logically, are understood to beimplemented by computer programs or equivalent electrical circuits,microcode, or the like. Furthermore, it has also proven convenient attimes to refer to these arrangements of operations as modules, withoutloss of generality. The described operations and their associatedmodules may be embodied in software, firmware, hardware, or anycombinations thereof.

Certain steps, operations, or processes described herein may beperformed or implemented with one or more hardware or software modules,alone or in combination with other devices. In some embodiments, asoftware module is implemented with a computer program productcomprising a computer-readable medium containing computer program code,which can be executed by a computer processor for performing any or allsteps, operations, or processes described.

In some embodiments, systems comprise a computer and/or data storageprovided virtually (e.g., as a cloud computing resource). In particularembodiments, the technology comprises use of cloud computing to providea virtual computer system that comprises the components and/or performsthe functions of a computer as described herein. Thus, in someembodiments, cloud computing provides infrastructure, applications, andsoftware as described herein through a network and/or over the internet.In some embodiments, computing resources (e.g., data analysis,calculation, data storage, application programs, file storage, etc.) areremotely provided over a network (e.g., the internet; CAVH, IRIS, or CAHcommunications; and/or a cellular network). See, e.g., U.S. Pat. App.Pub. No. 20200005633, incorporated herein by reference.

Embodiments of the technology may also relate to an apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes and/or it may comprise ageneral-purpose computing device selectively activated or reconfiguredby a computer program stored in the computer. Such a computer programmay be stored in a non-transitory, tangible computer readable storagemedium or any type of media suitable for storing electronicinstructions, which may be coupled to a computer system bus.Furthermore, any computing systems referred to in the specification mayinclude a single processor or may be architectures employing multipleprocessor designs for increased computing capability.

Additional embodiments will be apparent to persons skilled in therelevant art based on the teachings contained herein.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presenttechnology will become better understood with regard to the followingdrawings.

FIG. 1 is a schematic drawing showing an exemplary relationship of CAVH,IRIS, CAV, and IICS. 101, Connected automated vehicle highway systems(CAVH); 102, Intelligent road infrastructure system (IRIS); 103,Intelligent information conversion system (IICS); 104, Connected andautomated vehicle (CAV). Coding, decoding, and data flow are indicatedby arrows.

FIG. 2 is a schematic drawing showing an exemplary structure of a systemcomprising IRIS, CAVs, and IICS. 201, Intelligent road infrastructuresystem (IRIS); 202, Intelligent information conversion system (IICS);203, CAV (e.g., V1.5 CAV), which connects to IRIS; 204, CAV (e.g., V2CAV), which connects to IRIS. 205, CAV (e.g., V1.5 CAV), which does notconnect to IRIS; 206, CAV (e.g., V2 CAV), which does not connect toIRIS; 207, CAV (e.g., V3 CAV), which connects to IRIS; 208, CAV (e.g.,V4 CAV), which connects to IRIS. Connections of CAV with IRIS (e.g.,through the IICS) are shown by arrows.

FIG. 3 is a drawing showing an exemplary overall structure of the IICSand shows exemplary interactions of the IICS with IRIS and CAV. 301,Intelligent road infrastructure system (IRIS); 302, Intelligentinformation conversion system (IICS); 303, Information decoding; 304,Connection (e.g., communication and/or data flow) between IICS and CAV;305, Connected and automated vehicle; 306, Information encoding; 307,Code Book; 308, Connection (e.g., communication and/or data flow)between IICS and IRIS.

FIG. 4 is a schematic drawing showing exemplary hardware subsystems,modules, connections, and/or functions of an intelligent on-board unit;sensing information and/or data collected by the intelligent on-boardunit; and/or communications and/or data flow within the intelligenton-board unit. 401, Subsystem for sensing the driving environment; 402,Subsystem for sensing the internal environment of the vehicle; 403,Lidar sensor; 404, Vision sensor; 405, Millimeter-wave radar sensor;406, Other sensors; 407, Controller Area Network (CAN); 408, InertialMeasurement Unit (IMU)/Global Positioning System (GPS); 409, Otherdevices; 410, Scene information collected for the three-dimensionalpoint cloud data; 411, color (e.g., RGB) information collected forestablishing a three-dimensional simulation model; 412, Vehicleoperation information and surrounding target information; 413, Othersensing information; 414, Vehicle speed and yaw angle information; 415,Vehicle location information; 416, Other vehicle working conditionsinformation; 417, On-board sensing information transmitted to IICS andon-board control system; 418, Intelligent Road Infrastructure System(IRIS); 419, Intelligent Information Conversion System (IICS); 420,Environment sensing fusion module that fuses information from vehiclesand roadside; 421, Scene recognition module; 422, Decision-makingmodule; 423, Execution module; 424, Influence on the execution modulefrom IICS is based on the intelligence level of vehicles; 425,Information feedback to IICS for backup.

FIG. 5 is a schematic drawing showing an exemplary IRIS and IRIS dataflows. 501, Communication module of RIU; 502, RIU Interface module; 503,RIU Sensing module; 504, TCU Communication module; 505, TCU Dataprocessing module; 506, TCC; 507, TCU; 508, Intelligent InformationConversion System and Method for Collaborative Automatic Driving; 509,Data flow between RIU Communication module and IICS; 510, Data flow fromRIU Interface module to RIU Communication module; 511, Data flow fromRIU Sensing module to RIU Interface module; 512, Data flow from RIUCommunication module to TCU Communication module; 513, Data flow fromTCU Data processing module to TCU Communication module; 514, Data flowfrom TCU Communication module to TCU Data processing module; 515, Dataflow between a first TCU (e.g., Communication module of the first TCU)and a second TCU; 516, Data flow between a first TCU (e.g.,Communication module of the first TCU) and TCC; 517, Data flow between asecond TCU and TCC; 518, RIU.

FIG. 6 is a schematic drawing showing a vehicle-end connector for a V1.5CAV. 601, Traffic Control Center (TCC)/Traffic Control Unit (TCU); 602,Roadside Units (RIU); 603, Intelligent Information Conversion System(IICS); 604, Vehicle Intelligent Unit (VIU) of V1.5 CAV; 605, Executionmodule; 606, Sensing module of V1.5 CAV; 607, Sensing informationcommunicated from the roadside units to TCC/TCU; 608, Sensinginformation communicated from IICS to TCC/TCU; 609, Decision informationcommunicated from TCC/TCU to IICS; 610, Sensing information communicatedfrom VIU of V1.5 CAV to IICS; 611, Decision information communicatedfrom IICS to VIU of V1.5 CAV; 612, Sensing information communicated fromsensing module to VIU of V1.5 CAV.

FIG. 7 is a schematic drawing showing a vehicle-end connector for a V2and/or V3 CAV. 701, Traffic Control Center (TCC)/Traffic Control Unit(TCU); 702, Roadside Units (RIU); 703, Intelligent InformationConversion System (IICS); 704, On-board control system; 705, VehicleIntelligent Unit (VIU) of V2 and/or V3 CAV; 706, Execution module; 707,Sensing module of V2 and/or V3 CAV; 708, Sensing informationcommunicated from the roadside units to TCC/TCU; 709, Sensinginformation communicated from IICS to TCC/TCU; 710, Decision informationcommunicated from TCC/TCU to IICS; 711, Sensing information communicatedfrom VIU and/or on-board control system to IICS; 712, Decisioninformation communicated from IICS to VIU and/or on-board controlsystem; 713, Sensing information communicated from sensing module to VIUand/or on-board control system.

FIG. 8 is a schematic drawing showing a vehicle-end connector of a V4CAV. 801, Roadside units (RIU); 802, Traffic Control Center(TCC)/Traffic Control Unit (TCU); 803, Intelligent InformationConversion System (IICS); 804, Vehicle Intelligent Unit (VIU) of V4 CAV;805, On-board control system; 806, Sensing module of V4 CAV; 807,Execution module; 808, Sensing information communicated from theroadside units to TCC/TCU; 809, Sensing information communicated fromTCC/TCU to IICS; 810, Sensing information communicated from IICS to VIUand/or on-board control system; 811, Sensing information communicatedfrom sensing module to VIU and/or on-board control system.

FIG. 9 is a schematic drawing showing a system and process for accessingcertification. 901, Trusted agency that provides reliable information;902, Vehicle Intelligent Unit (VIU); 903, a certain (first) RIU fromwhich a vehicle intends to access certification; 904, confirmation ofcertification; 905, a new (second) RIU from which the vehicle intends toaccess certification; 906, confirmation of cross-domain certification;907, authorized registration provided by the trusted agency; 908,Published certificate and identity sent by VIU to the certain (first)RIU; 909, process of cross-certification; 910, Information serializationbackup sent by the certain RIU to the agency; 911, Serializedinformation sent by VIU to a new (second) RIU; 912, Transmission ofinformation from the new (second) RIU to the agency; 913, Validationresults provided by the agency to the new (second) RIU.

It is to be understood that the figures are not necessarily drawn toscale, nor are the objects in the figures necessarily drawn to scale inrelationship to one another. The figures are depictions that areintended to bring clarity and understanding to various embodiments ofapparatuses, systems, and methods disclosed herein. Wherever possible,the same reference numbers will be used throughout the drawings to referto the same or like parts. Moreover, it should be appreciated that thedrawings are not intended to limit the scope of the present teachings inany way.

DETAILED DESCRIPTION

Provided herein is technology relating to automated driving andparticularly, but not exclusively, to an intelligent informationconversion system and related methods for providing collaborativeautomatic driving to intelligent transportation systems, vehiclenetworking systems, collaborative management control systems,vehicle-road collaborative systems, automated driving systems, and thelike.

In this detailed description of the various embodiments, for purposes ofexplanation, numerous specific details are set forth to provide athorough understanding of the embodiments disclosed. One skilled in theart will appreciate, however, that these various embodiments may bepracticed with or without these specific details. In other instances,structures and devices are shown in block diagram form. Furthermore, oneskilled in the art can readily appreciate that the specific sequences inwhich methods are presented and performed are illustrative and it iscontemplated that the sequences can be varied and still remain withinthe spirit and scope of the various embodiments disclosed herein.

All literature and similar materials cited in this application,including but not limited to, patents, patent applications, articles,books, treatises, and internet web pages are expressly incorporated byreference in their entirety for any purpose. Unless defined otherwise,all technical and scientific terms used herein have the same meaning asis commonly understood by one of ordinary skill in the art to which thevarious embodiments described herein belongs. When definitions of termsin incorporated references appear to differ from the definitionsprovided in the present teachings, the definition provided in thepresent teachings shall control. The section headings used herein arefor organizational purposes only and are not to be construed as limitingthe described subject matter in any way.

Definitions

To facilitate an understanding of the present technology, a number ofterms and phrases are defined below. Additional definitions are setforth throughout the detailed description.

Throughout the specification and claims, the following terms take themeanings explicitly associated herein, unless the context clearlydictates otherwise. The phrase “in one embodiment” as used herein doesnot necessarily refer to the same embodiment, though it may.Furthermore, the phrase “in another embodiment” as used herein does notnecessarily refer to a different embodiment, although it may. Thus, asdescribed below, various embodiments of the invention may be readilycombined, without departing from the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or” operatorand is equivalent to the term “and/or” unless the context clearlydictates otherwise. The term “based on” is not exclusive and allows forbeing based on additional factors not described, unless the contextclearly dictates otherwise. In addition, throughout the specification,the meaning of “a”, “an”, and “the” include plural references. Themeaning of “in” includes “in” and “on.”

As used herein, the terms “about”, “approximately”, “substantially”, and“significantly” are understood by persons of ordinary skill in the artand will vary to some extent on the context in which they are used. Ifthere are uses of these terms that are not clear to persons of ordinaryskill in the art given the context in which they are used, “about” and“approximately” mean plus or minus less than or equal to 10% of theparticular term and “substantially” and “significantly” mean plus orminus greater than 10% of the particular term.

As used herein, disclosure of ranges includes disclosure of all valuesand further divided ranges within the entire range, including endpointsand sub-ranges given for the ranges.

As used herein, the suffix “-free” refers to an embodiment of thetechnology that omits the feature of the base root of the word to which“-free” is appended. That is, the term “X-free” as used herein means“without X”, where X is a feature of the technology omitted in the“X-free” technology. For example, a “calcium-free” composition does notcomprise calcium, a “mixing-free” method does not comprise a mixingstep, etc.

Although the terms “first”, “second”, “third”, etc. may be used hereinto describe various steps, elements, compositions, components, regions,layers, and/or sections, these steps, elements, compositions,components, regions, layers, and/or sections should not be limited bythese terms, unless otherwise indicated. These terms are used todistinguish one step, element, composition, component, region, layer,and/or section from another step, element, composition, component,region, layer, and/or section. Terms such as “first”, “second”, andother numerical terms when used herein do not imply a sequence or orderunless clearly indicated by the context. Thus, a first step, element,composition, component, region, layer, or section discussed herein couldbe termed a second step, element, composition, component, region, layer,or section without departing from technology.

As used herein, the word “presence” or “absence” (or, alternatively,“present” or “absent”) is used in a relative sense to describe theamount or level of a particular entity (e.g., component, action,element). For example, when an entity is said to be “present”, it meansthe level or amount of this entity is above a pre-determined threshold;conversely, when an entity is said to be “absent”, it means the level oramount of this entity is below a pre-determined threshold. Thepre-determined threshold may be the threshold for detectabilityassociated with the particular test used to detect the entity or anyother threshold. When an entity is “detected” it is “present”; when anentity is “not detected” it is “absent”.

As used herein, an “increase” or a “decrease” refers to a detectable(e.g., measured) positive or negative change, respectively, in the valueof a variable relative to a previously measured value of the variable,relative to a pre-established value, and/or relative to a value of astandard control. An increase is a positive change preferably at least10%, more preferably 50%, still more preferably 2-fold, even morepreferably at least 5-fold, and most preferably at least 10-foldrelative to the previously measured value of the variable, thepre-established value, and/or the value of a standard control.Similarly, a decrease is a negative change preferably at least 10%, morepreferably 50%, still more preferably at least 80%, and most preferablyat least 90% of the previously measured value of the variable, thepre-established value, and/or the value of a standard control. Otherterms indicating quantitative changes or differences, such as “more” or“less,” are used herein in the same fashion as described above.

As used herein, the term “number” shall mean one or an integer greaterthan one (e.g., a plurality).

As used herein, a “system” refers to a plurality of real and/or abstractcomponents operating together for a common purpose. In some embodiments,a “system” is an integrated assemblage of hardware and/or softwarecomponents. In some embodiments, each component of the system interactswith one or more other components and/or is related to one or more othercomponents. In some embodiments, a system refers to a combination ofcomponents and software for controlling and directing methods. Forexample, a “system” or “subsystem” may comprise one or more of, or anycombination of, the following: mechanical devices, hardware, componentsof hardware, circuits, circuitry, logic design, logical components,software, software modules, components of software or software modules,software procedures, software instructions, software routines, softwareobjects, software functions, software classes, software programs, filescontaining software, etc., to perform a function of the system orsubsystem. Thus, the methods and apparatus of the embodiments, orcertain aspects or portions thereof, may take the form of program code(e.g., instructions) embodied in tangible media, such as floppydiskettes, CD-ROMs, hard drives, flash memory, or any othermachine-readable storage medium wherein, when the program code is loadedinto and executed by a machine, such as a computer, the machine becomesan apparatus for practicing the embodiments. In the case of program codeexecution on programmable computers, the computing device generallyincludes a processor, a storage medium readable by the processor (e.g.,volatile and non-volatile memory and/or storage elements), at least oneinput device, and at least one output device. One or more programs mayimplement or utilize the processes described in connection with theembodiments, e.g., through the use of an application programminginterface (API), reusable controls, or the like. Such programs arepreferably implemented in a high-level procedural or object-orientedprogramming language to communicate with a computer system. However, theprogram(s) can be implemented in assembly or machine language, ifdesired. In any case, the language may be a compiled or interpretedlanguage, and combined with hardware implementations.

As used herein, the term “automated driving system” (abbreviated “ADS”)refers to a system that performs driving tasks (e.g., lateral andlongitudinal control of the vehicle) for a vehicle and thus allows avehicle to drive with reduced human control of driving tasks and/orwithout human control of driving tasks.

As used herein, the term “Connected Automated Vehicle Highway System”(“CAVH System”) refers to a comprehensive system (e.g., an ADS)providing full vehicle operations and control for connected andautomated vehicles (CAV), and, more particularly, to a systemcontrolling CAV by sending individual vehicles with detailed andtime-sensitive control instructions for vehicle following, lanechanging, route guidance, and related information. A CAVH systemcomprises sensing, communication, and control components connectedthrough segments and nodes that manage an entire transportation system.CAVH systems comprise four control levels: vehicle; roadside unit (RSU),which, in some embodiments, is similar to or the same as a roadsideintelligent unit (RIU); traffic control unit (TCU); and traffic controlcenter (TCC). See U.S. Pat. Nos. 10,380,886; 10,867,512; and/or10,692,365, each of which is incorporated herein by reference.

As used herein, the term “Intelligent Road Infrastructure System”(“IRIS”) refers to a system that facilitates vehicle operations andcontrol for CAVH systems. See U.S. Pat. Nos. 10,867,512 and/or10,692,365, each of which is incorporated herein by reference. In someembodiments, an IRIS provides transportation management and operationsand individual vehicle control for connected and automated vehicles(CAV). For example, in some embodiments, an IRIS provides a system forcontrolling CAV by sending individual vehicles with customized,detailed, and time-sensitive control instructions and trafficinformation for automated vehicle driving, such as vehicle following,lane changing, route guidance, and other related information.

As used herein, the term “GPS” refers to a global navigation satellitesystem (GNSS) that provides geolocation and time information to areceiver. Examples of a GNSS include, but are not limited to, the GlobalPositioning System developed by the United States, Differential GlobalPositioning System (DGPS), BeiDou Navigation Satellite System (BDS)System, GLONASS Global Navigation Satellite System), European UnionGalileo positioning system, the NavIC system of India, and theQuasi-Zenith Satellite System (QZSS) of Japan.

As used herein, the term “vehicle” refers to any type of poweredtransportation device, which includes, and is not limited to, anautomobile, truck, bus, motorcycle, or boat. The vehicle may normally becontrolled by an operator or may be unmanned and remotely orautonomously operated in another fashion, such as using controls otherthan the steering wheel, gear shift, brake pedal, and accelerator pedal.

As used herein, the term “automated vehicle” (abbreviated as “AV”)refers to an automated vehicle in an automated mode, e.g., at any levelof automation (e.g., as defined by SAE International Standard J3016,“Taxonomy and Definitions for Terms Related to Driving AutomationSystems for On-Road Motor Vehicles” (published in 2014 (J3016_201401)and as revised in 2016 (J3016_201609) and 2018 (J3016_201806), each ofwhich is incorporated herein by reference)).

As used herein, the term “allocate”, “allocating”, and similar termsreferring to resource distribution also include distributing, arranging,providing, managing, assigning, controlling, and/or coordinatingresources.

As used herein, the term “resource” refers to computational capacity(e.g., computational power, computational cycles, etc.); memory and/ordata storage capacity;

sensing capacity; communications capacity (e.g., bandwidth, signalstrength, signal fidelity, etc.); and/or electrical power.

As used herein, the term “service” refers to a process, a function thatperforms a process, and/or to a component or module that is configuredto provide a function that performs a process.

As used herein, the term “connected vehicle” or “CV” refers to aconnected vehicle, e.g., configured for any level of communication(e.g., V2V, V2I, and/or I2V).

As used herein, the term “connected and autonomous vehicle” or “CAV”refers to an autonomous vehicle that is able to communicate with othervehicles (e.g., by V2V communication), with roadside intelligent units(RIU), traffic control signals, and/or other infrastructure (e.g., anADS or component thereof) or devices. That is, the term “connectedautonomous vehicle” or “CAV” refers to a connected autonomous vehiclehaving any level of automation (e.g., as defined by SAE InternationalStandard J3016 (2014)) and communication (e.g., V2V, V2I, and/or I2V).

As used herein, the term “data fusion” refers to integrating a pluralityof data sources to provide information (e.g., fused data) that is moreconsistent, accurate, and useful than any individual data source of theplurality of data sources.

As used herein, the term “configured” refers to a component, module,system, subsystem, etc. (e.g., hardware and/or software) that isconstructed and/or programmed to carry out the indicated function.

As used herein, the terms “determine,” “calculate,” “compute,” andvariations thereof, are used interchangeably to any type of methodology,processes, mathematical operation, or technique.

As used herein, the term “reliability” refers to a measure (e.g., astatistical measure) of the performance of a system without failureand/or error. In some embodiments, reliability is a measure of thelength of time and/or number of functional cycles a system performswithout a failure and/or error.

As used herein, the term “support” when used in reference to one or morecomponents of an ADS, CAVH, CAV, and/or a vehicle providing support toand/or supporting one or more other components of the ADS, CAVH, CAV,and/or a vehicle refers to, e.g., exchange of information and/or databetween components and/or levels of the ADS, CAVH, CAV, and/or avehicles; sending and/or receiving instructions between componentsand/or levels of the ADS, CAVH, CAV, and/or a vehicles; and/or otherinteraction between components and/or levels of the ADS, CAVH, CAV,and/or a vehicles that provide functions such as information exchange,data transfer, messaging, and/or alerting.

As used herein, the term “ADS component” or “component of an ADS” refersindividually and/or collectively to one or more of components of an ADSand/or a CAVH system, e.g., a VIU, RIU, TCC, TCU, TCC/TCU, TOC, CAV, asupporting subsystem, and/or a cloud component.

As used herein, the term “roadside intelligent unit” (abbreviated “RIU”)may refer to one RIU, a plurality of RIU, and/or a network of RIU.

As used herein, the term “critical point” refers to a portion or regionof a road that is identified as appropriate to be provided embodimentsof the function allocation technology provided herein. In someembodiments, a critical point is categorized as a “static criticalpoint” and in some embodiments, a critical point is categorized as a“dynamic critical point”. As used herein, a “static critical point” is apoint (e.g., region or location) of a road that is a critical pointbased on identification of road and/or traffic conditions that aregenerally constant or that change very slowly (e.g., on a time scalelonger than a day, a week, or a month) or only by planned reconstructionof infrastructure. As used herein, a “dynamic critical point” is a point(e.g., region or location) of a road that is a critical point based onidentification of road conditions that change (e.g., predictably or notpredictably) with time (e.g., on a time scale of an hour, a day, a week,or a month). Critical points based on historical crash data, trafficsigns, traffic signals, traffic capacity, and road geometry areexemplary static critical points. Critical points based on trafficoscillations, real-time traffic management, or real-time trafficincidents are exemplary dynamic critical points.

In some embodiments, critical points are identified using, e.g.,historical crash data (e.g., the top 20% (e.g., top 15-25% (e.g., top15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25%)) most frequent crashpoints in a road system are identified as critical points); trafficsigns (e.g., where certain traffic signs (e.g., accident-prone areas)are detected are identified as critical points); traffic capacity (e.g.,the top 20% (e.g., top 15-25% (e.g., top 15, 16, 17, 18, 19, 20, 21, 22,23, 24, or 25%)) highest traffic capacity areas are identified ascritical points); road geometry (e.g., roads with critical road geometry(e.g., curves, blind spots, hills, intersections (e.g., signalizedintersections, stop sign intersections, yield sign intersections),roundabouts) are identified as critical points); traffic oscillation(e.g., points with significant traffic oscillations are identified ascritical points); real-time traffic management (e.g., points withpotential traffic management are identified as critical points); and/orreal-time traffic incident (e.g., points with traffic incidents (e.g.,accident, crash, congestion, construction or maintenance,weather-related event, etc.) or vehicle malfunction are identified ascritical points).

As used herein, the terms “microscopic”, “mesoscopic”, and “macroscopic”refer to relative scales in time and space. In some embodiments, thescales include, but are not limited to, a microscopic level relating toindividual vehicles (e.g., longitudinal movements (car following,acceleration and deceleration, stopping and standing) and lateralmovements (lane keeping, lane changing)), a mesoscopic level relating toroad corridors and/or segments (e.g., special event early notification,incident prediction, merging and diverging, platoon splitting andintegrating, variable speed limit prediction and reaction, segmenttravel time prediction, and/or segment traffic flow prediction), and amacroscopic level relating to an entire road network (e.g., predictionof potential congestion, prediction of potential incidents, predictionof network traffic demand, prediction of network status, prediction ofnetwork travel time). In some embodiments, a time scale at a microscopiclevel is from 1 to 10 milliseconds and is relevant to tasks such asvehicle control instruction computation. In some embodiments, a timescale at a mesoscopic level is typically from 10 to 1000 millisecondsand is relevant to tasks such as incident detection and pavementcondition notification. In some embodiments, a time scale at amacroscopic level is longer than 1 second and is relevant to tasks suchas route computing.

As used herein, the automation and/or intelligence levels of vehicles(V), infrastructure (I), and system (S) are described with respect to an“intelligence level” and/or an “automation level”.

For example, in some embodiments, the intelligence and/or automationlevel of a vehicle (e.g., a CAV) is defined according to SAEInternational Standard J3016, “Taxonomy and Definitions for TermsRelated to Driving Automation Systems for On-Road Motor Vehicles”(published in 2014 (J3016_201401) and as revised in 2016 (J3016_201609)and 2018 (J3016_201806)), each of which is incorporated herein byreference. For example, in some embodiments, the intelligence and/orautomation level of a vehicle (e.g., a CAV) is defined as one of thefollowing: V0: No automation functions (e.g., “manual driving”); V1:Basic functions to assist a human driver to control a vehicle (e.g.,“assisted driving”); V2: Functions to assist a human driver to control avehicle for simple tasks and to provide basic sensing functions (e.g.,“partially autonomous driving”); V3: Functions to sense the environmentin detail and in real-time and to complete relatively complicateddriving tasks (e.g., “conditional autonomous driving”); V4: Functions toallow vehicles to drive independently under limited conditions andsometimes with human driver backup (e.g., “highly autonomous driving”);and V5: Functions to allow vehicles to drive independently without humandriver backup under all conditions (e.g., “fully autonomous driving”).As used herein, a vehicle having an intelligence level of 1.5 (V1.5)refers to a vehicle having capabilities between vehicle intelligence 1and vehicle intelligence level 2, e.g., a vehicle at V1.5 has minimal orno automated driving capability but comprises capabilities and/orfunctions (e.g., hardware and/or software) that provide control of theV1.5 vehicle by a CAVH system (e.g., the vehicle has “enhanced driverassistance” or “driver assistance plus” capability).

In some embodiments, the classification of infrastructure (e.g.,Intelligent Road Infrastructure System (IRIS)) is defined according toinformatization (e.g., capabilities and functions related todigitalization and/or networking), intelligence (e.g., capabilities andfunctions related to traffic operation and/or management), automation(e.g., capabilities and functions related to assisted driving and/orautonomous driving), application scenarios (e.g., capabilities relatedto functional effectiveness and efficiency in terms of time and/orspace), capabilities and functions related to management of mixedtraffic comprising vehicles having a range of automation levels, and/orsafety (e.g., capabilities and functions related to safety warning,avoidance, and/or collision avoidance).

In some embodiments, the infrastructure intelligence and/or automationlevel is one of the following: I0: No functions (e.g.,“non-informatization” and/or “non-intelligence” and/or“non-automation”); I1: Information collection and traffic managementwherein the infrastructure provides primitive sensing functions in termsof aggregated traffic data collection and basic planning and decisionmaking to support simple traffic management at low spatial and temporalresolution (e.g., “preliminary digitization” and/or “preliminaryintelligence” and/or “preliminary automation”); I2: I2X and vehicleguidance for driving assistance, wherein, in addition to functionsprovided in I1, the infrastructure realizes limited sensing functionsfor pavement condition detection and vehicle kinematics detection, suchas lateral and/or longitudinal position, speed, and/or acceleration, fora portion of traffic, in seconds or minutes; the infrastructure alsoprovides traffic information and vehicle control suggestions andinstructions for the vehicle through I2X communication (e.g., “partialnetworking” and/or “partial intelligence” and/or “partial automation”);I3: Dedicated lane automation, wherein the infrastructure providesindividual vehicles with information describing the dynamics ofsurrounding vehicles and other objects on a millisecond time scale andsupports full automated driving on CAVH-compatible vehicle dedicatedlanes; the infrastructure has limited transportation behavior predictioncapability (e.g., “conditional autonomous driving” and/or “highlynetworked driving based on road infrastructure”); I4: Scenario-specificautomaton wherein the infrastructure provides detailed drivinginstructions for vehicles to realize full automated driving in certainscenarios and/or areas, such as locations comprising predefinedgeo-fenced areas, where the traffic is mixed (e.g., comprises automatedand non-automated vehicles); essential vehicle-based automationcapability, such as emergency braking, is provided as a backup system incase the infrastructure fails (e.g., “highly autonomous driving based onroad infrastructure”); and I5: Full infrastructure automation whereinthe infrastructure provides full control and management of individualvehicles under all scenarios and optimizes a whole road network wherethe infrastructure is deployed; vehicle automation functionality is notnecessary provided as a backup; full active safety functions areavailable (e.g., “fully autonomous driving based on roadinfrastructure”).

In some embodiments, the system intelligence and/or automation level isone of the following: S0: no function (e.g., “non-informatization”and/or “non-intelligence” and/or “non-collaboration” and/or“non-integration”); S1: the system provides simple functions forindividual vehicles such as cruise control and passive safety function;the system detects the vehicle speed, location, and distance (e.g.,“preliminary informatization” and/or “preliminary intelligence” and/or“preliminary collaboration” and/or “preliminary integration”); S2: thesystem comprises individual intelligence and detects vehicle functioningstatus, vehicle acceleration, and/or traffic signs and signals;individual vehicles make decisions based on their own information andhave partially automated driving to provide complicated functions suchas assisting vehicle adaptive cruise control, lane keeping, lanechanging, and automatic parking (e.g., “partial informatization” and/or“partial intelligence” and/or “partial collaboration” and/or “partialintegration”); S3: the system integrates information from a group ofvehicles and behaves with ad-hoc intelligence and prediction capability,the system has intelligence for decision making for the group ofvehicles and can complete complicated conditional automated drivingtasks such as cooperative cruise control, vehicle platooning, vehiclenavigation through intersections, merging, and diverging (e.g., “highinformatization” and/or “high intelligence” and/or “high collaboration”and/or “conditional system integration”); S4: the system integratesdriving behavior optimally within a partial network; the system detectsand communicates detailed information within the partial network andmakes decisions based on both vehicle and transportation informationwithin the network and handles complicated, high level automated drivingtasks, such as navigating traffic signal corridors, and provides optimaltrajectories for vehicles within a small transportation network (e.g.,“full informatization” and/or “full intelligence” and/or “fullcollaboration” and/or “high degree of system integration”); S5: vehicleautomation and system traffic automation, wherein the system optimallymanages an entire transportation network; the system detects andcommunicates detailed information within the transportation network andmakes decisions based on all available information within the network;the system handles full automated driving tasks, including individualvehicle tasks and transportation tasks, and coordinates all vehicles tomanage traffic (e.g., “full informatization” and/or “full intelligence”and/or “full collaboration” and/or “full system integration”). In someembodiments, the system dimension is dependent on the vehicle andinfrastructure dimensions, e.g., as represented by the followingequation (S=system automation; V=vehicle intelligence; andI=infrastructure intelligence):

S=f(V,I)

In some embodiments, vehicle intelligence is provided by and/or relatedto the CAV Subsystem and the infrastructure intelligence is provided byand/or related to the CAH Subsystem. One of ordinary skill in the artmay refer to SAE International Standard J3016, “Taxonomy and Definitionsfor Terms Related to Driving Automation Systems for On-Road MotorVehicles” (published in 2014 (J3016_201401) and as revised in 2016(J3016_201609) and 2018 (J3016_201806)), which provides additionalunderstanding of terms used in the art and herein.

DESCRIPTION

The technology described herein provides an Intelligent InformationConversion System (IICS) and related methods. In some embodiments, e.g.,as shown in FIGS. 1-3, the IICS facilitates communication betweenintelligent road infrastructure (e.g., IRIS) and vehicles (e.g., CAV) ata range of intelligence levels (e.g., V1, V1.5, V2, V3, and V4) inautomatic driving systems (ADS). Accordingly, the IICS improves theservice level of ADS and/or provides functions and support to meet theautonomous driving requirements for systems comprising CAV and ADS. Insome embodiments, the IICS provides real-time dynamic informationexchange between intelligent road infrastructure (e.g., IRIS) andvehicles (e.g., CAV) at a range of intelligence levels (e.g., V1, V1.5,V2, V3, and V4) in automatic driving systems (ADS). In some embodiments,the IICS comprises a code book, a coding module, a connector module, anda supporting system. In some embodiments, the code book providesinformation sorting, the coding module provides encoding and decodingfunctions encode and/or decode information using the code book (e.g.,using tables, translation tools, and other information provided by thecode book). In some embodiments, the connector module comprises aroadside connector and/or a vehicle-end connector. In some embodiments,the supporting system comprises a cache system and/or a power supplysystem. In some embodiments, the IICS provides systems and methodsconfigured to provide service for different levels of ADS. In someembodiments, the IICS is configured to be integrated into the IRISand/or a cloud platform.

Code Book and Code Book Information Standard

In some embodiments, e.g., as shown in FIG. 3, the IICS technologyprovided herein comprises and/or provides a “code book”. In someembodiments, the code book provides an information standard for encodinginformation transmitted to and/or from an ADS. In some embodiments, thecode book provides an information standard for encoding informationtransmitted to and/or from a CAV. Accordingly, in some embodiments, thecode book provides a standard for communicating information betweendifferent CAV and/or between different ADS that each may haveinformation coding schemes specific for the CAV and/or ADS. Thus, insome embodiments, the code book provides an intermediate (e.g.,universal) standard for information exchange between any CAV and anyADS.

In some embodiments, a code book string comprises a series of integersrepresenting specific information about a CAV, road infrastructure,and/or information. In some embodiments, a code book string comprises anordered series of integers (e.g., 16 integers ordered from left toright) representing a number of categories of information (e.g., 16categories of information), wherein the position (e.g., position 1, 2,3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16 from left to right)of the integer within the code book string indicates the category ofinformation represented by the integer and the value of each integerrepresents a specific value for a (e.g., each) category.

Accordingly, in some embodiments, a code book string comprises asequence (e.g., an ordered sequence) of integers to represent specificcategories of information describing a CAV, the road and/orinfrastructure with which the CAV interacts and from which the CAVreceives support for automated driving, and/or information exchangedbetween a CAV and/or infrastructure. For example, in some embodiments, acode book string comprises a plurality of integers (e.g., an orderedsequence of integers) describing the categories of: e.g., vehicleautomation level, vehicle original equipment manufacturer (OEM), vehiclebrand, vehicle model year, vehicle type, road category, highway level,urban road level, road intelligence level; information function level(sensing, forecasting, decision-making, and control, etc.); and/ordescribing the six information categories of information category I(frequency), information category II (safety demand), informationcategory III (precision), information category IV (scope), informationcategory V (static and dynamic), and/or information category VI (name).

In some embodiments, a code book string comprises a string of integers(e.g., 16 integers in the order of categories specified above) andrepresents a specific message and/or information. In some embodiments,each category has a number of values represented by an integer (e.g., 0,1, 2, 3, 4, 5, 6, 7, 8, 9, . . . , N). Accordingly, the position of theinteger in the code book string (e.g., position 1, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, or 16) indicates the category of theinformation represented by the integer and the value of the integer ateach position (e.g., 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, . . . , N) representsthe specific value for the category.

For example, in some embodiments, the vehicle automation level categorymay have a value of V0, V1, V2, V3, V4, or V5 that is represented by theintegers 0, 1, 2, 3, 4, or 5, respectively. As another example, thecategory vehicle OEM may have a value of factory 1, factory 2, . . . ,or factory N that is represented by the integers 1, 2, . . . , or N,respectively. In particular, in some embodiments, the 16 categories ofdata provided by a code book string and the values and integersrepresenting each value for each of the 16 categories are provided inTable 1.

TABLE 1 Code book string categories, values, and integers Integers Coderepresenting book values of the string Code book Values of the code bookinteger information code book information position category informationcategory category 1 Vehicle V0, V1, V2, V3, 1, 2, 3, 4, or 5, automationV4, or V5 respectively level 2 Vehicle factory 1, factory 2, 1, 2, . .., or N, OEM . . . , or factory N respectively 3 Vehicle brand 1, brand2, 1, 2, . . ., or N, brand . . . , or brand N respectively 4 Vehiclecar, bus, truck, . . . , 1, 2, 3, . . ., or N, type or vehicle type Nrespectively 5 Road highway or 1 or 2, category urban road respectively6 Highway expressway, 0, 1, 2, 3, or 4, level first-class highway,respectively second-class highway, third-class highway, or fourth-classhighway 7 Urban road urban expressway, 0, 1, 2, or 3, level majorarterial, respectively minor arterial, or collector road 8 Road IO, I1,I2, I3, 1, 2, 3, 4, or 5, (infrastructure) I4, or I5 respectivelyintelligence level 9 Information sensing, forecasting, 0, 1, 2, or 3,function decision- respectively type making, or vehicle control 10Information high frequency, 0, 1, or 2, category I medium frequency,respectively (frequency) or low frequency 11 Information high safety 0,1, or 2, category II demand, medium respectively (safety safety demand,demand) or low safety demand 12 Information high precision, 0, 1, or 2,category III medium precision, respectively (precision) or low precision13 Information network level, 0, 1, or 2, category IV road segmentlevel, respectively (scope) or vehicle level 14 Information static ordynamic 0 or 1, category V (static respectively or dynamic) 15Information name 1, name 2, 1, 2, . . ., or N category VI . . . , orname N (name)

In some embodiments, code book strings are sorted and/or filteredaccording to one or more values at one or more code book stringpositions. For example, in some embodiments, the technology providessystems and methods for sorting a code book string using informationcategory I (frequency). In particular, the code book string categoryinformation category (I) relates to the frequency that the informationrepresented by the code book string changes. In some embodiments, aservice section information, toll station information, a lane width, aroad sign meaning, and/or a road curvature are categorized as lowfrequency information. In addition, in some embodiments, road condition,vehicle spacing and headway, relative distance, relative speed, lateraldeviation, and/or longitudinal deviation are categorized as highfrequency information.

In some embodiments, the technology provides systems and methods forsorting a code book string using information category II (safetydemand). In particular, the code book string category informationcategory II (safety demand) relates to the degree of importance of theinformation for decision making, vehicle control, and motion planning ofCAV for automated driving. In some embodiments, lateral distance,longitudinal headway, lateral deviation, longitudinal deviation,relative distance, and/or relative velocity are categorized as highsafety demand information. In some embodiments, ramp information,service section information, toll station information, dedicated laneinformation, toll lane information, HOV lane information, a number oflanes, a lane width, and/or a traffic sign are categorized as low safetydemand.

In some embodiments, information relating to a vehicle is categorized ashigh frequency, medium frequency, or low frequency information and/or ashigh safety demand, medium safety demand, or low safety demandinformation according to the frequency and safety demand level, e.g., asdescribed in Table 2.

TABLE 2 Vehicle information categorized by frequency and safety demandHigh Frequency Medium Frequency Low Frequency High InformationInformation for Information Safety for an an individual describingDemand individual vehicle describing pedestrians vehicle velocity, andother describing position, road traffic participants lateral distance,control, engine around an longitudinal torque control, individualheadway, braking-stable vehicle lateral deviation, acceleration,longitudinal start-stop control, deviation, throttle force relativedistance, relative velocity Medium Information Information Trafficaccident, Safety describing the describing road trajectory Demand roadconditions obstacles and/or planning, for an right of way weatherindividual distribution information vehicle around an individual vehicleLow Information Ramp information, Road Safety relating to the serviceinfrastructure, Demand effective section information, road curvature,tracking of a toll station number target (e.g., information, of lanesand vehicle, dedicated lane, lane width, surrounding HOV lane trafficsign vehicle, object, etc.)

In some embodiments, information relating to road infrastructure orconditions is categorized as high frequency, medium frequency, or lowfrequency information and/or as high safety demand, medium safetydemand, or low safety demand information according to the frequency andsafety demand level, e.g., as described in Table 3.

TABLE 3 Road information categorized by frequency and safety demand HighFrequency Medium Frequency Low Frequency High Road condition, road Roadaverage speed, Road Safety obstacle, vehicle average headway,infrastructure Demand control command congestion status, (e.g., throttleforce, driving environment, braking force, and/or brightnessinformation, steering wheel traffic event adjustment angle) informationMedium Traffic control Road average Vehicle Safety information speedcondition Demand information Low Weather Trajectory Safety informationinformation, Demand road network information

In some embodiments, the technology provides systems and methods forsorting a code book string using information category III (precision).In particular, the code book string category information category III(precision) relates to driving scenarios, driving tasks, and/or vehicleintelligence levels. For example, in some embodiments, a trackingtarget, collision residual time, lateral deviation, longitudinaldeviation, and/or velocity information are categorized as high precisionlevel information. In some embodiments, the number of lanes, lane width,weather information, ramp information, and service section informationare categorized as low precision information.

In some embodiments, the technology provides systems and methods forsorting a code book string using information category IV (scope). Inparticular, the code book string category information category IVrelates to a spatial scale. For example, in some embodiments, roadnetwork level information, (e.g., road condition, traffic accidentinformation, road sign meaning, obstacle information, number of lanes,lane width, weather information, and/or map information) is categorizedas macroscopic information. In some embodiments, road section levelinformation (e.g., road section average speed and/or road sectionaverage volume) is categorized as mesoscopic information. In someembodiments, vehicle level information (e.g., information foreffectively tracking a target (e.g., an individual vehicle, surroundingvehicles, objects)), time to collision, vehicle identity and/oridentifier, individual vehicle speed, individual vehicle relativedistance, individual vehicle relative speed, individual vehicle lateraldeviation, individual vehicle longitudinal deviation, individual vehicleengine torque control, individual vehicle braking stable acceleration,individual vehicle start-stop control, and/or throttle force) iscategorized as microscopic information.

In some embodiments, vehicle information is classified according toprecision (high precision, medium precision, or low precision) and/orscope (network level, road section level, or vehicle level), e.g., asdescribed in Table 4.

TABLE 4 Vehicle information categorized by precision and scope HighPrecision Medium Precision Low Precision Road Road condition,Inter-vehicle Number of Network traffic spacing, lanes, lane Levelaccident individual width, (macroscopic) information, position, weather,road road sign individual infrastructure, meaning, road velocity, rampcurvature, target vehicle information, lane velocity, service commandtarget vehicle section information, position, information, road obstaclerelative distance, toll station information relative velocity,information, lateral exclusive deviation, lane, toll longitudinal lanedeviation, information, surrounding HOV lane pedestrian informationposition, speed information, meaning of traffic sign, engine torquecontrol, braking stable acceleration, start stop control, throttle forceRoad Road section engine torque Number of Section average speed control,lanes, lane Level braking stable width, weather (mesoscopic)acceleration, information, start stop road control, throttleinfrastructure, force ramp information, service section information,toll station information, exclusive lane, toll lane information, HOVlane information Vehicle Inter-vehicle Road condition, Number of Levelspacing, traffic lanes, lane (microscopic) individual position,accident, width, weather, individual road sign road velocity, targetmeaning, road infrastructure, vehicle curvature, ramp, velocity, targetlane service vehicle position, command section, toll relative distance,information, station, exclusive relative velocity, road obstacle lane,toll lateral deviation, lane, HOV longitudinal lane deviation,surrounding pedestrian position, speed information, meaning of trafficsign, engine torque control, braking stable acceleration, start-stopcontrol, throttle force

In some embodiments, information relating to road infrastructure orconditions is categorized according to precision (high precision, mediumprecision, or low precision) and/or scope (network level, road sectionlevel, or vehicle level), e.g., as described in Table 5.

TABLE 5 Road information categorized by precision and scope HighPrecision Medium Precision Low Precision Road Vehicle condition Roadaverage Number of Network information speed, ramps, service Level(vehicle identity average section (macroscopic) and/or identifier,headway, information, vehicle intelligence congestion HOV level) status,driving lane environment, information, brightness etc. information,traffic event information, road condition, weather information, roadinfrastructure, ramp information, throttle force, braking force,steering wheel adjustment angle Road Vehicle condition throttle force,Number of Section information braking force, ramps, Level (vehicleidentity steering wheel service (mesoscopic) and/or identifier,adjustment sections, vehicle intelligence angle HOV level), trafficcontrol lanes, etc. information (variable speed limit) Vehicle Vehiclecondition Network Number of Level information information ramps,(microscopic) (vehicle service identity and/or section, identifier,vehicle HOV lane intelligence etc. level), trajectory planning, throttleforce, braking force, steering wheel adjustment angle

In some embodiments, the technology provides systems and methods forsorting a code book string using information category V (static ordynamic). In particular, the code book string category informationcategory V relates to information that is unchanged during vehicleoperation (static information) or to information that changes duringvehicle operation (dynamic information). For example, in someembodiments, service section location, number of lanes, lane width, HOVlane location, vehicle condition information (e.g., vehicle class,vehicle identity and/or identifier, etc.), road alignment, speed bump,insulating joist, safety guards, anti-dazzle plate, traffic markings andsigns, and/or ramp location is categorized as static information. Insome embodiments, average road speed, average headway, congestionstatus, weather information, traffic control information, trajectoryplanning, road network information, and/or throttle strength iscategorized as dynamic information.

In some embodiments, vehicle information is classified according tobeing static or dynamic (e.g., temporally changing or unchanging) and/orfunction level (sensing information, prediction information,decision-making information, or control information), e.g., as providedin Table 6.

TABLE 6 Vehicle information categorized as static or dynamic and byfunction level Static Information Dynamic Information Sensing WeatherInter-vehicle spacing, information, road individual position, individualcondition, road velocity, target vehicle velocity, infrastructure,target vehicle position, relative ramp, road distance, relativevelocity, obstacle, service lateral deviation, longitudinal section,toll deviation, surrounding station, road sign pedestrian position,speed meaning, number information, meaning of traffic of lanes, lanesign width, dedicated lane, toll lane, HOV lane, road curvature, roadsign meaning Prediction Long term and short term prediction of vehicletrajectory Decision- Information relating to Making effectively trackinga target, longitudinal safety, collision residual time, lateral safety,lateral vehicle cut-in factor, origin and/or destination, collision-freeoptimal path, right of way distribution Control Throttle force, brakingforce, steering wheel adjustment angle

In some embodiments, road information is classified according to beingstatic or dynamic (e.g., temporally changing or unchanging) and/orfunction level (sensing information, prediction information,decision-making information, or control information), e.g., as providedin Table 7.

TABLE 7 Road information categorized as static or dynamic and byfunction level Static Information Dynamic Information Sensing Vehiclecondition Road average speed, average information headways, congestionstatus, (including vehicle weather information, driving identity and/orenvironment brightness identifier, vehicle information, traffic eventintelligence information level), weather, road condition, roadinfrastructure, ramp Prediction Traffic control information (variablespeed limit etc.), average speed Decision- Trajectory planning, networkMaking information Control Throttle force, braking force, steering wheeladjustment angle

In some embodiments, vehicle and/or road information has a value forinformation category VI (name). In some embodiments, the value ofinformation category VI (name) is a name describing the information, anidentifier and/or descriptor of information, e.g., vehicle speed,vehicle position, etc. In some embodiments, the value of category VI(name) is a value that is not provided by one of the other 15 categoriesencoded by the first 15 integers of a code book string. In someembodiments, the technology provides systems and methods for sorting acode book string using information category VI (name).

In some embodiments, the IICS connects IRIS and CAV of any intelligencelevel in automatic driving systems (ADSs) to improve the service levelof ADS and to meet different automatic driving requirements for variousCAV and ADS. In some embodiments, the IICS provides real-time dynamicinformation interaction between IRIS and vehicles. In some embodiments,the IICS comprises a code book and provides a function for code bookstring information sorting; a coding module configured to provideencoding and decoding functions for converting information from CAVand/or ADS to and from the code book standardized format for informationexchange; a connector module comprising a roadside connector and thevehicle-end connector; and a supporting system comprising a cache systemand a power supply system. In some embodiments, the supporting systemcomprises a cache system and a power consumption system. In someembodiments, the cache system is configured to cache data transmitted tothe system and, in some embodiments, the power supply system providesthe energy required for the operation of the entire system. In someembodiments, the IICS comprises systems and methods configured toprovide automated driving service for any intelligence level of ADS. Insome embodiments, the IICS is configured to integrate into an IRISand/or a cloud platform.

In some embodiments, the code book standardized format for informationexchange comprises a sequence of numbers corresponding to categories ofvehicle automation level, original equipment manufacturer, vehiclebrand, vehicle model year, vehicle type, road category, highway level,urban road level, road intelligence level, information function level,information category I (frequency), information category II (safetydemand), information category III (precision), information category IV(scope), information category V (static and dynamic), and informationcategory VI (name).

In some embodiments, the coding module provides and/or facilitatesreal-time dynamic information exchange between the vehicle end (e.g.,CAV of any intelligence level) and the road end (e.g., road sectionsequipped with IRIS), wherein the coding module encodes information fromCAV to IRIS and decodes information from IRIS to CAV using the code bookstandardized format for information exchange.

In some embodiments, when a CAV is driving on a road section serviced byIRIS, a VIU of the CAV transmits vehicle end information and theinformation demands to the IICS through the connector. Thus, the VIUprovides information transmission between CAV and the IICS. The vehicleend information comprises basic vehicle information (e.g., for accessverification), vehicle sensing information (e.g., for informationfusion), vehicle current control command information (e.g., for vehicleroad collaborative sensing and control), and vehicle driving taskexecution information (e.g., for vehicle driving command optimization).The IICS encodes the received information and then transmits the encodedinformation to IRIS through the connector to provide informationinteraction from the vehicle end to the road end.

Next, after receiving the encoded information through the connector,IRIS extracts the personalized information from the vehicle end byparsing the integers and positions of integers in the code book stringand fuses roadside information (e.g., detected by the IRIS) with thevehicle end information encoded by the IICS and received by IRIS fromthe IICS connector. The fused information (e.g., encoded into a codebook string formatted using the code book standardized format forinformation exchange) is transmitted by IRIS to the IICS through theIICS connector. The IICS decodes the fused information according to thecode book standardized format for information exchange to extractpersonalized information (e.g., vehicle intelligence level, OEM, vehiclebrand, vehicle model year, vehicle type, etc.) and the informationdemands (e.g., frequency, safety demand, precision, scope, and/or staticor dynamic. Then, IICS transmits the decoded information to CAV throughthe IICS connector, thus responding to the information demand from thevehicle end and providing information exchange from the road end to thevehicle end.

As described below, in some embodiments, the technology relates to anintelligent information conversion system (IICS) for an intelligent roadinfrastructure, e.g., an Intelligent Road Infrastructure System (IRIS)(e.g., as described in U.S. Pat. Nos. 10,867,512 and/or 10,692,365, eachof which is incorporated herein by reference). In some embodiments, theIRIS has a hierarchical structure comprising a number of RIU (e.g.,configured to receive vehicle-side information from IICS and performdata exchange with a TCU); a number of TCU (e.g., configured to interactwith RIU, other TCU, cloud, and/or TCC (e.g., a cloud TCC) forinformation exchange; and to perform data fusion and processing); and/ora TCC (e.g., a cloud TCC) (e.g., configured to perform decision-making(e.g., traffic control)) and data storage. See, e.g., FIG. 5.

In some embodiments, the RIU comprises a sensing module (e.g.,comprising a camera, a radar (e.g., microwave radar), and/or othersensors) configured to collect traffic and/or vehicle drivingenvironment information within the road section; an interaction (e.g.,exchange) module (e.g., configured to integrate data from the sensingmodule and the communication module and/or to send data to thecommunication module); a communication module (e.g., configured toreceive data from the interaction module and/or to exchange data withthe TCU communication module). See, e.g., FIG. 5.

In some embodiments, the TCU comprises a data processing module (e.g.,configured to fuse data received from the TCU communication module(e.g., traffic control information, vehicle road sensing information(e.g., received from the roadside communication module), informationfrom other TCU, and traffic state information (e.g., traffic flow,speed, and/or congestion)); and/or configured to process fused data andmake decisions using the fused data); and/or a communication module(e.g., configured to exchange data with the data processing moduleand/or communication modules of other TCU (e.g., point and/or segmentTCU)). In some embodiments, the TCU communication module does notdirectly communicate with the communication module of IICS. See, e.g.,FIG. 5.

In some embodiments, CAV comprise a vehicle-end connector comprising anenvironment sensing module (e.g., configured to sense the surroundingenvironment of the CAV and to interact with and collect data fromvarious sensors); an internal environment sensing module (e.g.,configured to sense the working conditions of the CAV and to interactwith and collect data from various sensors); a cognitive module (e.g.,configured to collect semantic information and/or cognitive informationaround the vehicle using integrated sensor information and roadsideinformation from IICS (e.g., driving area, obstacle types and locations,and driving trajectories)); a decision-making module (e.g., configuredto provide control decisions (e.g., using previous data stored in thevehicle control system; machine learning based on previous experience;and/or a direct mapping relationship of the information and/orinstructions obtained from the roadside infrastructure by the IICS to anintelligent vehicle control quantity)). In some embodiments, the CAVcomprise a vehicle-end connector configured to perform and/or supportsensing the environment around the CAV, e.g., wherein CAV sensors sensethe surrounding environment of the CAV and an environment sensing fusionmodule integrates CAV sensor data with roadside information and/orsensor data from IICS to recognize and/or characterize the environmentaround the CAV and/or scene information around the CAV; and/or topredict the trajectory of the CAV.

In some embodiments, IRIS issues control commands to the executionmodules of CAV at intelligence levels of, e.g., V1, V1.5, V2, V3, V4, orhigher (e.g., V5) through the IICS. In some embodiments, e.g., as shownin FIG. 6, the IICS is configured to support and/or facilitate automateddriving for CAV at low intelligence level (e.g., V1, V1.5), wherein theIRIS and IICS coordinate to provide complete, sufficiently complete,and/or essentially complete information integration and decision-makingtasks and to send decision-making plans and control instructions to CAV.In some embodiments, when the CAV collaborates with road infrastructureto provide an automated driving function, the TCC/TCU receives sensinginformation from the RIU and/or receives sensing information from thevehicle (e.g., from the vehicle VIU); the IRIS makes a decision (e.g.,based on the road environment, road geometry information, and thevehicle driving information from TICS); and the IRIS issuesvehicle-specific and time-sensitive control instructions through IICS toCAV; and the CAV performs vehicle control operations according to thedecision information and/or vehicle-specific and time-sensitive controlinstructions sent by IICS. In some embodiments, data and/or informationprovided by roadside infrastructure sensors supports the decision-makingof TCC/TCU. In some embodiments, the vehicle-end information and/or dataprovides feedback to verify and/or to adjust the decision-making (e.g.,to provide data for machine learning).

In some embodiments, e.g., as shown in FIG. 7, the IICS is configured tosupport and/or facilitate automated driving for CAV at mediumintelligence levels (e.g., V2 and V3), wherein the VIU exchanges dataand/or information with IICS based on the information requirements ofthe driving task; and/or the roadside information and/or data providedthrough IICS helps the VIU to perform automated driving tasks. In someembodiments, the IICS provides storage of previous decisions, controlinstructions, and automated driving outcomes resulting from the previousdecisions and/or control instructions to improve the accumulation ofprevious decisions, control instructions, and automated driving outcomesresulting from the previous decisions and/or control instructions, e.g.,to provide data for machine learning. In some embodiments, the IICSprovides machine learning to modify previous decisions and/or controlinstructions to provide improved automated driving control decisionsand/or control instructions to VIU (e.g., to adapt automated driving tomore types of driving environments), thus providing a strategy fordriving task collaboration.

In some embodiments, e.g., as shown in FIG. 7, the IICS is configured tosupport and/or facilitate automated driving for CAV at mediumintelligence levels (e.g., V2 and V3) by facilitating collaborativeautomated driving between CAV and an intelligent road section to providea specific automated driving function. For example, in some embodiments,a TCC/TCU receives sensing information from a RIU and/or VIU; the IRIStransmits information through the IICS to VIU; and the VIU transmitsvehicle control instructions to the vehicle on-board control system andvehicle execution module, which provides mechanical control of thevehicle. In some embodiments, the TCC/TCU receives information and/ordata from the roadside infrastructure and/or vehicle-end informationand/or data through the IICS, and the vehicle on-board control systemoperates the vehicle according to vehicle status information, roadgeometry information, target object information, and the vehicleexperience memory. In some embodiments, the vehicle on-board controlsystem facilitates system collaboration (e.g., collaboration between CAVand ADS) by providing support and assistance to IRIS to produce andissue appropriate operating instructions; in some embodiments, IRISfacilitates collaboration (e.g., collaboration between CAV and ADS) byproviding support and assistance to the on-board control system toproduce and issue appropriate operating instructions.

In some embodiments, e.g., as shown in FIG. 8, the IICS is configured tosupport and/or facilitate automated driving for CAV at high intelligencelevels (e.g., V4 and above). For example, in some embodiments, the IICSsends roadside sensing information and/or data to the VIU to providesupport and assistance to the vehicle control system. In someembodiments, TCC/TCU receives sensing information and/or data from RIU(e.g., only from RIU) when CAV perform vehicle-road collaboration on anintelligent road section to provide a specific automated drivingfunction. In some embodiments, the TCC/TCU and the vehicle on-boardcontrol system sense traffic information and/or driving behaviorinformation relatively independently; and the vehicle control systemreceives sensing information and/or data from the VIU and/or roadsidesensing information and/or data transmitted by IICS and makes a decisionindependently. In some embodiments, roadside sensing information and/ordata are transmitted to VIU through IICS, and the information and/ordata are transmitted to the on-board control system to assist thevehicle control system to produce and issue control and decisioninformation to the execution module.

In some embodiments, a control execution result is transmitted to IRISthrough IICS for data backup and/or to provide feedback to verify and/orto adjust the decision-making.

In some embodiments, the IRIS receives vehicle sensing informationtransmitted by IICS and receives sensing information from roadsideinfrastructure. The TCU/TCC provides a driving behavior decision plan,control instructions are formulated, and the plan and/or controlinstructions are issued by IICS.

In some embodiments, the IRIS, IICS, and the vehicle-end hardwarecommunicate with each other using their respective communication modulesand one or more communication technologies (e.g., including but notlimited to a dedicated short-range communication technology (DSRC), 4G,5G, and 6G).

In some embodiments, the technology provides methods for classifyinginformation based on one or more of information frequency, safetydemand, precision, spatial scope, and/or being static or dynamic (e.g.,being changing or unchanging in time). In some embodiments, thetechnology provides methods for classifying information based on two ormore of information frequency, safety demand, precision, spatial scope,and/or being static or dynamic (e.g., being changing or unchanging intime). See, e.g., Tables 2-7.

In some embodiments, the technology provides methods for classifyinginformation based on information frequency (e.g., classifyinginformation as high frequency information, medium frequency information,or low frequency information). In some embodiments, the technologyprovides methods for classifying information based on safety demand,which relates to the degree of importance for information during theprocess of decision making, motion planning, and control for automateddriving. In some embodiments, methods comprise classifying informationbased on precision, which relates to driving scenarios, driving tasks,and vehicle intelligence levels. In some embodiments, the technologyprovides methods for classifying information based on spatial scope(e.g., classifying information as macroscopic information relating toroad network level information, mesoscopic information relating to roadsection level information, or microscopic information relating tovehicle level information). In some embodiments, the technology providesmethods for classifying information based on the information beingstatic (e.g., information unchanged during the operation of the vehicle)or dynamic (e.g., information changed during the method and/or duringoperation of the vehicle).

Access Certification

In some embodiments, e.g., as shown in FIG. 9, CAV (e.g., a CAV in anIRIS road segment) interacts with a resource provided by another trusteddomain through a process for certifying access and/or using an accesscertification system. In some embodiments, access certification providespermission to a CAV to access IRIS resources. In some embodiments,access certification is mutual (e.g., cross-domain) certificationbetween two ADS (e.g., between a first IRIS and a second IRIS, betweenan IRIS and another ADS, between a first ADS and a second ADS). In someembodiments, certification (e.g., mutual certification) establishes(e.g., quickly establishes) a trust relationship in a current domainusing trust information in a previous domain. In some embodiments, thetechnology provides a method for certification (e.g., mutualcertification). In some embodiments, a method for certificationcomprises authorizing a CAV (e.g., by a trusted agency), e.g., to obtaina certificate and/or information for offline registration of the CAV asa certified (e.g., trusted) CAV. In some embodiments, the method formutual certification comprises providing a first certification byverifying the legal status of an RIU when a CAV enters a jurisdictionserviced by the RIU. In some embodiments, verifying the legal status ofan RIU comprises comparing the status of an RIU servicing a presentjurisdiction to the status of the RIU servicing the jurisdiction intowhich the CAV is entering. In some embodiments, a VIU of a CAV verifiesthe status of an RIU when a CAV comprising the VIU enters a jurisdictionservices by the RIU. In some embodiments, the method for certificationcomprises using anonymous information for interaction verification ofthe CAV with the RIU. In some embodiments, the VIU of the CAV usesanonymous information for interactive verification of the CAV with theRIU. For example, in some embodiments, the RIU serializes a pseudonymand/or information associated with the verifying VIU and stores thepseudonym and/or information associated with the verifying VIU in thesystem. In some embodiments, the method for certification comprisesauthenticating the CAV with a RIU when the CAV enters a new jurisdictionserviced by the RIU. For example, in some embodiments, authenticatingthe CAV with a RIU comprises a VIU of the CAV providing the pseudonymand/or information identifying the VIU to the RIU; the RIU querying thecertification system and/or trusted agency using the pseudonym and/orinformation identifying the VIU; and the RIU receiving verificationresults from the trusted agency and/or system that identifies the VIU asa certified (e.g., trusted) VIU and, accordingly, provides the mutual(e.g., cross-domain) certification of the CAV with the RIU.

CAV Sensors and Sensing

In some embodiments, CAV comprises a number of sensors, a number ofsensing capabilities, and/or are configured to perform a number ofsensing functions. In some embodiments, e.g., as shown in FIG. 4, CAVcomprise an on-board unit (e.g., a VIU) comprising an externalenvironment (e.g., driving environment) sensing module and/or aninternal environment sensing module. In some embodiments, the externalenvironment sensing module is configured to operate with sensorsincluding, e.g., lidar, vision sensors, radar (e.g., millimeter-waveradar), and other sensors. In some embodiments, CAV are configured toprovide (e.g., transmit, communicate, send) information and/or data fromsensors to the IICS. Accordingly, in some embodiments, CAV comprise acommunications module configured to communicate with IICS (e.g., acommunications module of the IICS) and/or to transmit sensor data and/orother information to the IICS (e.g., a communications module of theIICS).

For example, in some embodiments, a CAV lidar sensor collects and/orrecords depth information and/or three-dimensional point cloud data(e.g., in some embodiments, a CAV lidar sensor collects and/or recordsthree-dimensional point cloud data with associated reflectionintensities). In some embodiments, the CAV and/or lidar transmits thedepth information and the three-dimensional point cloud data (e.g.,further comprising associated reflection intensities) to IICS.

In some embodiments, a CAV vision sensor collects and/or records color(e.g., RGB) information of a scene and/or provides (e.g., constructs) athree-dimensional simulation model based on the geometric informationsensed from the environment. In some embodiments, the CAV and/or visionsensor transmits color (e.g., RGB) information of a scene and/or sendsthe three-dimensional simulation model to IICS.

In some embodiments, a CAV radar (e.g., millimeter-wave radar) sensorcollects operation information and/or the location of the CAV and/orcollects information about objects around the CAV. In some embodiments,the CAV and/or radar (e.g., millimeter-wave radar) transmits thelocation of the CAV and/or transmit information about objects around theCAV to IICS.

In some embodiments, a CAV auxiliary sensor and/or auxiliary sensingsystem collects operation information and/or the location of the CAVand/or collects information about objects around the CAV. In someembodiments, the CAV auxiliary sensor and/or auxiliary sensing systemtransmits the location of the CAV and/or transmit information aboutobjects around the CAV to IICS.

In some embodiments, the internal environment sensing module isconfigured to operate and/or communicate with various devices and/orfunctions including, e.g., a Controller Area Network (CAN) and/or anInertial Measurement Unit (IMU)/Global Positioning System (GPS)component. For example, in some embodiments, the CAN obtains a speedand/or a yaw angle information of a CAV. In some embodiments, the CANtransmits a speed and/or a yaw angle information of a CAV to a sensingfusion module. In some embodiments, the IMU/GPS component obtains theprecise location information of a CAV, e.g., using the GPS for generalpositioning (e.g., because GPS error does not accumulate) and/or the IMUis used for short-term real-time positioning.

Intelligent Road Infrastructure Systems

In some embodiments, the technology relates to an intelligentinformation conversion system (IICS) for an intelligent roadinfrastructure, e.g., an Intelligent Road Infrastructure System (IRIS)(e.g., as described in U.S. Pat. Nos. 10,867,512 and/or 10,692,365, eachof which is incorporated herein by reference). An IRIS which facilitatesvehicle operations and control for connected automated vehicle highway(CAVH) systems. In some embodiments, an IRIS provides vehicles withindividually customized information and real-time control instructionsfor vehicles to fulfill driving tasks, e.g., car following, lanechanging, and route guidance. Further, in some embodiments, IRIS systemsand methods manage transportation operations and management services forboth freeways and urban arterials. In some embodiments, IRIS manages aportion of lanes or all lanes of a highway. In some embodiments, IRISprovides vehicle-specific control instructions and/or vehicle-specificinformation to CAV (e.g., to a VIU of a CAV).

In some embodiments, IRIS comprise or consist of one of more of thefollowing subsystems: (1) Roadside intelligent unit (RIU) network; (2)Traffic Control Unit (TCU) and Traffic Control Center (TCC) network;(TCU/TCC network); (3) vehicle intelligent unit (VIU); (4) trafficoperations centers (TOC); and/or (5) cloud information and computingservices. In some embodiments, IRIS manages one or more of the followingfunction categories: sensing, transportation behavior prediction andmanagement, planning and decision making, and vehicle control. In someembodiments, IRIS is supported by real-time wired and/or wirelesscommunication, power supply networks, and cyber safety and securityservices.

Accordingly, IRIS provides a comprehensive system configured to providefull vehicle operations and control for CAV and/or CAVH systems bysending individual vehicles with detailed and time-sensitive controlinstructions. In some embodiments, vehicle-specific instructions and/orinformation are constructed and/or optimized by a TCC, passed from theTCC to a TCU, sent by the TCU to the RIU network, and distributed by RIUto CAV (e.g., transmitted to a VIU of a CAV). Thus, the IRIS comprisesTCC, TCU, and RIU in a hierarchical structure that provides coverageover different spatial scales.

Although the disclosure herein refers to certain illustratedembodiments, it is to be understood that these embodiments are presentedby way of example and not by way of limitation. All publications andpatents mentioned in the above specification are herein incorporated byreference in their entirety for all purposes. Various modifications andvariations of the described compositions, methods, and uses of thetechnology will be apparent to those skilled in the art withoutdeparting from the scope and spirit of the technology as described.Although the technology has been described in connection with specificexemplary embodiments, it should be understood that the invention asclaimed should not be unduly limited to such specific embodiments.Indeed, various modifications of the described modes for carrying outthe invention that are obvious to those skilled in the art are intendedto be within the scope of the following claims.

1-94. (canceled)
 95. An intelligent information conversion system (IICS)configured to: connect an automatic driving system (ADS) and a connectedand automated vehicle (CAV); and provide real-time dynamic informationexchange between ADS and CAV.
 96. The IICS of claim 95, wherein the IICSimproves the service level of an ADS from a first service level to asecond service level, wherein the first service level is not adequate toprovide automatic driving for a CAV and the second service level isadequate to provide automatic driving for said CAV.
 97. The IICS ofclaim 95, wherein said IICS comprises a code book providing astandardized format for information exchange.
 98. The IICS of claim 95,configured to sort information in a code book string, encode informationinto a code book string, or decode information from a code book string.99. The IICS of claim 95, comprising an encoding/decoding moduleconfigured to: encode information into a code book string or decodeinformation from a code book string; facilitate real-time dynamicinformation interaction between CAV and ADS; facilitate real-timedynamic information interaction between CAV and road infrastructure; orexchange information between CAV and ADS by encoding informationreceived from a CAV and/or ADS into a code book string; and by decodinga code book string into information for transmission to a CAV and/orADS.
 100. The IICS of claim 95, comprising: a road-side connectorcomponent configured to exchange information between the IICS androadside infrastructure; and a vehicle-side connector componentconfigured to exchange information between the IICS and a vehicle. 101.The IICS of claim 97, wherein said standardized format for informationexchange comprises a sequence of integers, wherein each integer has avalue corresponding to a value of a category including vehicleautomation level, original equipment manufacturer, vehicle brand,vehicle model year, vehicle type, road category, highway level, urbanroad level, road intelligence level, information function level,information category I (frequency), information category II (safetydemand), information category III (precision), information category IV(scope), information category V (static and dynamic), or informationcategory VI (name).
 102. The IICS of claim 99, wherein said code bookstring has a format provided by a code book standardized format forinformation exchange.
 103. The IICS of claim 95, configured to receivevehicle information and/or information demands from a vehicle.
 104. TheIICS of claim 103, wherein said vehicle comprises a vehicle intelligenceunit (VIU).
 105. The IICS of claim 95, wherein said CAV comprises avehicle-end connector component.
 106. The IICS of claim 105, whereinsaid vehicle-end connector component comprises: an environment sensingmodule configured to sense the surrounding environment of the CAV;and/or to collect data from external vehicle sensors; an internalenvironment sensing module configured to sense the status of the CAV, tosense the internal environment of the CAV, and to sense the driverstatus; and/or to collect data from internal vehicle sensors; acognitive module configured to collect semantic information and/orcognitive information describing the CAV environment; and/or adecision-making module configured to provide vehicle control decisions.107. The IICS of claim 106, wherein said cognitive module is configuredto integrate vehicle sensor information and roadside infrastructureinformation from IICS.
 108. The IICS of claim 106, wherein saiddecision-making module is configured to make decisions based on storeddata, stored control decisions, and/or stored outcomes of controldecision execution.
 109. The IICS of claim 106, wherein the environmentsensing module is configured to integrate data and/or information fromvehicle sensors with data and/or information from roadsideinfrastructure sensors obtained from IICS to describe the vehicleenvironment and predict vehicle trajectory.
 110. The IICS of claim 95configured to assist CAV at intelligence level V1 or V1.5, wherein anIRIS and the IICS perform information integration and decision-making;and send vehicle control instructions to CAV.
 111. The IICS of claim 95configured to assist CAV at intelligence level V2 or V3, wherein a VIUexchanges information with IICS based on the information requirements ofa driving task; and roadside data and/or information provided throughIICS supports the VIU to complete a driving task.
 112. The IICS of claim95 configured to assist CAV at intelligence level V4 or above, whereinthe IICS transmits roadside sensing information and/or data to a VIU tosupport the CAV vehicle control system.
 113. The IICS of claim 101,configured to perform a method of classifying information based on thefrequency of update of the information to assign a value to informationcategory I (frequency) of high frequency, medium frequency, or lowfrequency.
 114. The IICS of claim 101, configured to perform a method ofclassifying information based on the safety demand of the informationcomprising assessing the importance of the information for decisionmaking, motion planning, and/or control of automated vehicles; andassigning a value to information category II (safety demand) of highsafety demand, medium safety demand, or low safety demand.
 115. The IICSof claim 101, configured to perform a method of classifying informationbased on precision of the information comprising assessing a drivingscenario, driving task, and/or vehicle intelligence level; and assigninga value to information category III (precision) of high precision,medium precision, or low precision.
 116. The IICS of claim 101,configured to perform a method of classifying information based on thescope of the information comprising assessing the scope of theinformation and assigning a value to information category IV (scope) ofmacroscopic, mesoscopic, or microscopic, wherein macroscopic informationcomprises road network level information; mesoscopic informationcomprises road section level information; and microscopic informationcomprises vehicle level information.
 117. The IICS of claim 101,configured to perform a method of classifying information based on thestatic or dynamic characteristics of the information comprisingassessing the dynamic and static characteristics of the information; andassigning a value to information category V (static or dynamic) ofstatic or dynamic, wherein static information comprises information thatis unchanged during the operation of the vehicle; and dynamicinformation comprises information that changes during the operation ofthe vehicle.